scholarly journals Source-Space Cross-Frequency Amplitude-Amplitude Coupling in Tinnitus

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Oliver Zobay ◽  
Peyman Adjamian
Keyword(s):  
Theta Rhythm ◽  
Low Frequency ◽  
Hearing Level ◽  
Thalamocortical Dysrhythmia ◽  
Thalamocortical Oscillations ◽  
Frequency Coupling ◽  
Auditory Cortices ◽  
Frequency Coherence ◽  
And Control ◽  
Cross Frequency Coupling

The thalamocortical dysrhythmia (TCD) model has been influential in the development of theoretical explanations for the neurological mechanisms of tinnitus. It asserts that thalamocortical oscillations lock a region in the auditory cortex into an ectopic slow-wave theta rhythm (4–8 Hz). The cortical area surrounding this region is hypothesized to generate abnormal gamma (>30 Hz) oscillations (“edge effect”) giving rise to the tinnitus percept. Consequently, the model predicts enhanced cross-frequency coherence in a broad range between theta and gamma. In this magnetoencephalography study involving tinnitus and control cohorts, we investigated this prediction. Using beamforming, cross-frequency amplitude-amplitude coupling (AAC) was computed within the auditory cortices for frequencies (f1,f2) between 2 and 80 Hz. We find the AAC signal to decompose into two distinct components at low (f1,f2<30 Hz) and high (f1,f2>30 Hz) frequencies, respectively. Studying the correlation of AAC with several key covariates (age, hearing level (HL), tinnitus handicap and duration, and HL at tinnitus frequency), we observe a statistically significant association between age and low-frequency AAC. Contrary to the TCD predictions, however, we do not find any indication of statistical differences in AAC between tinnitus and controls and thus no evidence for the predicted enhancement of cross-frequency coupling in tinnitus.

scholarly journals Electrophysiological Low-Frequency Coherence and Cross-Frequency Coupling Contribute to BOLD Connectivity

Neuron ◽  
2012 ◽  
Vol 76 (5) ◽  
pp. 1010-1020 ◽  
Author(s):  
Liang Wang ◽  
Yuri B. Saalmann ◽  
Mark A. Pinsk ◽  
Michael J. Arcaro ◽  
Sabine Kastner
Keyword(s):  
Low Frequency ◽  
Frequency Coupling ◽  
Frequency Coherence ◽  
Cross Frequency Coupling

scholarly journals Signature patterns for top-down and bottom-up information processing via cross-frequency coupling in macaque auditory cortex

2018 ◽  
Author(s):  
Christian D. Márton ◽  
Makoto Fukushima ◽  
Corrie R. Camalier ◽  
Simon R. Schultz ◽  
Bruno B. Averbeck
Keyword(s):  
Information Processing ◽  
Auditory Cortex ◽  
Predictive Coding ◽  
Low Frequency ◽  
Information Need ◽  
Top Down ◽  
Bottom Up ◽  
Low Frequencies ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

AbstractPredictive coding is a theoretical framework that provides a functional interpretation of top-down and bottom up interactions in sensory processing. The theory has suggested that specific frequency bands relay bottom-up and top-down information (e.g. “γ up, β down”). But it remains unclear whether this notion generalizes to cross-frequency interactions. Furthermore, most of the evidence so far comes from visual pathways. Here we examined cross-frequency coupling across four sectors of the auditory hierarchy in the macaque. We computed two measures of cross-frequency coupling, phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC). Our findings revealed distinct patterns for bottom-up and top-down information processing among cross-frequency interactions. Both top-down and bottom-up made prominent use of low frequencies: low-to-low frequency (θ, α, β) and low frequency-to-high γ couplings were predominant top-down, while low frequency-to-low γ couplings were predominant bottom-up. These patterns were largely preserved across coupling types (PAC and AAC) and across stimulus types (natural and synthetic auditory stimuli), suggesting they are a general feature of information processing in auditory cortex. Moreover, our findings showed that low-frequency PAC alternated between predominantly top-down or bottom-up over time. Altogether, this suggests sensory information need not be propagated along separate frequencies upwards and downwards. Rather, information can be unmixed by having low frequencies couple to distinct frequency ranges in the target region, and by alternating top-down and bottom-up processing over time.1SignificanceThe brain consists of highly interconnected cortical areas, yet the patterns in directional cortical communication are not fully understood, in particular with regards to interactions between different signal components across frequencies. We employed a a unified, computationally advantageous Granger-causal framework to examine bi-directional cross-frequency interactions across four sectors of the auditory cortical hierarchy in macaques. Our findings extend the view of cross-frequency interactions in auditory cortex, suggesting they also play a prominent role in top-down processing. Our findings also suggest information need not be propagated along separate channels up and down the cortical hierarchy, with important implications for theories of information processing in the brain such as predictive coding.

scholarly journals Thalamocortical dysrhythmia in intraoperative recordings of focal epilepsy

2019 ◽  
Vol 121 (6) ◽  
pp. 2020-2027 ◽  
Author(s):  
Daniel J. Martire ◽  
Simeon Wong ◽  
Mirriam Mikhail ◽  
Ayako Ochi ◽  
Hiroshi Otsubo ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
High Frequency ◽  
Large Scale ◽  
Focal Epilepsy ◽  
Critical Role ◽  
Epileptogenic Zone ◽  
Thalamocortical Dysrhythmia ◽  
High Frequency Activity ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

Resonant interactions between the thalamus and cortex subserve a critical role for maintenance of consciousness as well as cognitive functions. In states of abnormal thalamic inhibition, thalamocortical dysrhythmia (TCD) has been described. The characteristics of TCD include a slowing of resting oscillations, ectopic high-frequency activity, and increased cross-frequency coupling. Here, we demonstrate the presence of TCD in four patients who underwent resective epilepsy surgery with chronically implanted electrodes under anesthesia, continuously recording activity from brain regions at the periphery of the epileptogenic zone before and after resection. Following resection, we report an acceleration of the large-scale network resting frequency coincident with decreases in cross-frequency phase-amplitude coupling. Interregional functional connectivity in the surrounding cortex was also increased following resection of the epileptogenic focus. These findings provide evidence for the presence of TCD in focal epilepsy and highlight the importance of reciprocal thalamocortical oscillatory interactions in defining novel biomarkers for resective surgeries. NEW & NOTEWORTHY Thalamocortical dysrhythmia (TCD) occurs in the context of thalamic dysfacilitation and is characterized by slowing of resting oscillations, ectopic high-frequency activity, and cross-frequency coupling. We provide evidence for TCD in focal epilepsy by studying electrophysiological changes occurring at the periphery of the resection margin. We report acceleration of resting activity coincident with decreased cross-frequency coupling and increased functional connectivity. The study of TCD in epilepsy has implications as a biomarker and therapeutic target.

scholarly journals Perspectives of Non-Gaussianity in Atmospheric Synoptic and Low-Frequency Variability

2015 ◽  
Vol 28 (13) ◽  
pp. 5091-5114 ◽  
Author(s):  
Philip Sura ◽  
Abdel Hannachi
Keyword(s):  
Spatial Scales ◽  
Low Frequency ◽  
Atmospheric Sciences ◽  
Low Frequency Variability ◽  
Weather And Climate ◽  
Exact Shape ◽  
Gaussian Statistics ◽  
Frequency Coupling ◽  
Non Gaussian ◽  
Cross Frequency Coupling

Abstract Understanding non-Gaussian statistics of atmospheric synoptic and low-frequency variability has important consequences in the atmospheric sciences, not least because weather and climate risk assessment depends on knowing and understanding the exact shape of the system’s probability density function. While there is no doubt that many atmospheric variables exhibit non-Gaussian statistics on many time (and spatial) scales, a full and complete understanding of this phenomenon remains a challenge. Various mechanisms behind the observed atmospheric non-Gaussian statistics have been proposed but remain, however, multifaceted and scattered in the literature: nonlinear dynamics, multiplicative noise, cross-frequency coupling, nonlinear boundary layer drag, and others. Given the importance of this subject for weather and climate research, and in an attempt to contribute to this topic, a thorough review and discussion of the different mechanisms that lead to non-Gaussian weather and climate variability are presented in this paper and an outlook is given.

scholarly journals A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Jessica K Nadalin ◽  
Louis-Emmanuel Martinet ◽  
Ethan B Blackwood ◽  
Meng-Chen Lo ◽  
Alik S Widge ◽  
...  
Keyword(s):  
High Frequency ◽  
Statistical Power ◽  
Brain Activity ◽  
Low Frequency ◽  
Modeling Framework ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling ◽  
Frequency Phase

Cross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate examples of CFC during a seizure and in response to electrical stimuli.

scholarly journals A statistical modeling framework to assess cross-frequency coupling while accounting for confounding effects

2019 ◽  
Author(s):  
Jessica Nadalin ◽  
Louis-Emmanuel Martinet ◽  
Ethan Blackwood ◽  
Meng-Chen Lo ◽  
Alik S. Widge ◽  
...  
Keyword(s):  
Statistical Modeling ◽  
High Frequency ◽  
Statistical Power ◽  
Brain Activity ◽  
Low Frequency ◽  
Modeling Framework ◽  
Frequency Coupling ◽  
Cross Frequency Coupling ◽  
Frequency Phase

AbstractCross frequency coupling (CFC) is emerging as a fundamental feature of brain activity, correlated with brain function and dysfunction. Many different types of CFC have been identified through application of numerous data analysis methods, each developed to characterize a specific CFC type. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. To address this, we propose a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. We show in simulations that the proposed method successfully detects CFC between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples. Applying the method to in vivo data, we illustrate how CFC evolves during seizures and is affected by electrical stimuli.

scholarly journals A Time-Series Model of Phase Amplitude Cross Frequency Coupling and Comparison of Spectral Characteristics with Neural Data

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Kyle Q. Lepage ◽  
Sujith Vijayan
Keyword(s):  
Time Series ◽  
High Frequency ◽  
Spectral Characteristics ◽  
Low Frequency ◽  
Time Series Model ◽  
High Frequency Component ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

Stochastic processes that exhibit cross-frequency coupling (CFC) are introduced. The ability of these processes to model observed CFC in neural recordings is investigated by comparison with published spectra. One of the proposed models, based on multiplying a pulsatile function of a low-frequency oscillation (θ) with an unobserved and high-frequency component, yields a process with a spectrum that is consistent with observation. Other models, such as those employing a biphasic pulsatile function of a low-frequency oscillation, are demonstrated to be less suitable. We introduce the full stochastic process time series model as a summation of three component weak-sense stationary (WSS) processes, namely,θ,γ, andη, withηa1/fαnoise process. Theγprocess is constructed as a product of a latent and unobserved high-frequency processxwith a function of the lagged, low-frequency oscillatory component (θ). After demonstrating that the model process is WSS, an appropriate method of simulation is introduced based upon the WSS property. This work may be of interest to researchers seeking to connect inhibitory and excitatory dynamics directly to observation in a model that accounts for known temporal dependence or to researchers seeking to examine what can occur in a multiplicative time-domain CFC mechanism.

scholarly journals Delta-mediated cross-frequency coupling organizes oscillatory activity across the rat cortico-basal ganglia network

2013 ◽  
Vol 7 ◽  
Author(s):  
Jon López-Azcárate ◽  
María Jesús Nicolás ◽  
Ivan Cordon ◽  
Manuel Alegre ◽  
Miguel Valencia ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Oscillatory Activity ◽  
Frequency Coupling ◽  
Cross Frequency Coupling
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